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[D] Visualizing neural networks

x-posting from /r/tensorflow

Hi! I’m working on Tensorflow bindings for Luna (

We allow you to build ML models by connecting visual components together – every component can define a new network layer and its dependencies. The API is highly inspired by Keras functional API.

Here you can find an example of what it looks like

Luna has the ability to display visualizations below its components, so you could inspect the look of your network on each step (after adding the first layer, adding the second layer, etc). We want to provide interactive visualizations of the network you’ve built so far. I’d love to ask you what visualizations you would find the most helpful during building neural networks?

We were initially thinking about something like that – so you could see the structure of your network, the weights and activation functions, but we are very open for discussion here. We want to create something that would be helpful while building various kinds of networks.

Which features do you think are most important to visualize? The weights? The activations on each layer? Something else entirely?

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.